High frequency of microsatellite instability in young patients with head-and-neck squamous-cell carcinoma: Lack of involvement of the mismatch repair geneshMLH1 ANDhMSH2
Bibliographic record
Abstract
The most prevalent risk factors in the development of head-and-neck squamous-cell carcinoma (HNSCC) are excessive tobacco and alcohol consumption. In young patients with HNSCC, these risk factors are often absent. Our purpose was to investigate the risk factors, microsatellite instability (MSI) changes and status of the mismatch repair genes hMLH1 and hMSH2 in a cohort of young patients with HNSCC. Fifty-seven HNSCC tumors were examined for the presence of MSI at 16 microsatellite sites using PCR. In the young patient group (24 cases, < or = 44 years old), 100% of tumors had MSI at 1 site at least and 88% had MSI at 2 or more loci. In older patients (33 cases, > or = 45 years), MSI at 1 or more sites was found in 61% of tumors (young vs. old, p = 0.0003) and instability at 2 or more sites was found in 36% of tumors (young vs. old, p = 0.0001). The involvement of the mismatch repair genes was investigated by examining promoter methylation, exon mutation and gene expression of hMLH1 and hMSH2. All results were negative, indicating that inactivation of these 2 genes does not play a role in the development of MSI in tumors from this patient group. Furthermore, the young patient group had a significantly lower incidence of smoking (46% young, 88% old; p = 0.001) and alcohol consumption (33% young, 67% old; p = 0.0169), emphasizing the probable importance of other environmental and/or genetic factors in the development of their disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".